scholarly journals Beyond Statistical Analysis in Chaos-Based CSPRNG Design

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
John Prakash Arockiasamy ◽  
Lydia Elizabeth Benjamin ◽  
Rhymend Uthariaraj Vaidyanathan
Keyword(s):  
Statistical Analysis ◽  
Statistical Tests ◽  
Security Analysis ◽  
Statistical Testing ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Pseudorandom Sequences ◽  
Randomness Test ◽  
Modern Cryptography

The design of cryptographically secure pseudorandom number generator (CSPRNG) producing unpredictable pseudorandom sequences robustly and credibly has been a nontrivial task. Almost all the chaos-based CSPRNG design approaches invariably depend only on statistical analysis. Such schemes designed to be secure are being proven to be predictable and insecure day by day. This paper proposes a design and instantiation approach to chaos-based CSPRNG using proven generic constructions of modern cryptography. The proposed design approach with proper instantiation of such generic constructions eventually results in providing best of both worlds that is the provable security guarantees of modern cryptography and passing of necessary statistical tests as that of chaos-based schemes. Also, we introduce a new coupled map lattice based on logistic-sine map for the construction of CSPRNG. The proposed pseudorandom number generator is proven using rigorous security analysis as that of modern cryptography and tested using the standard statistical testing suites. It is observed that the generated sequences pass all stringent statistical tests such as NIST, Dieharder, ENT, and TestU01 randomness test suites.

scholarly journals A New Two-Dimensional Mutual Coupled Logistic Map and Its Application for Pseudorandom Number Generator

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Xuan Huang ◽  
Lingfeng Liu ◽  
Xiangjun Li ◽  
Minrong Yu ◽  
Zijie Wu
Keyword(s):  
Statistical Tests ◽  
Chaotic Map ◽  
Logistic Map ◽  
Security Analysis ◽  
Three Dimensional ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Two Dimensional ◽  
Practical Applications

Given that the sequences generated by logistic map are unsecure with a number of weaknesses, including its relatively small key space, uneven distribution, and vulnerability to attack by phase space reconstruction, this paper proposes a new two-dimensional mutual coupled logistic map, which can overcome these weaknesses. Our two-dimensional chaotic map model is simpler than the recently proposed three-dimensional coupled logistic map, whereas the sequence generated by our system is more complex. Furthermore, a new kind of pseudorandom number generator (PRNG) based on the mutual coupled logistic maps is proposed for application. Both statistical tests and security analysis show that our proposed PRNG has good randomness and that it can resist all kinds of attacks. The algorithm speed analysis indicates that PRNG is valuable to practical applications.

Design and Test of Pseudorandom Number Generator Using a Star Network of Lorenz Oscillators

2017 ◽  
Vol 27 (12) ◽  
pp. 1750184 ◽  
Author(s):  
Kenichiro Cho ◽  
Takaya Miyano
Keyword(s):  
Stream Cipher ◽  
Statistical Tests ◽  
New Method ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Lorenz Equations ◽  
Dynamical Models ◽  
Pseudorandom Numbers ◽  
Star Network

We have recently developed a chaos-based stream cipher based on augmented Lorenz equations as a star network of Lorenz subsystems. In our method, the augmented Lorenz equations are used as a pseudorandom number generator. In this study, we propose a new method based on the augmented Lorenz equations for generating binary pseudorandom numbers and evaluate its security using the statistical tests of SP800-22 published by the National Institute for Standards and Technology in comparison with the performances of other chaotic dynamical models used as binary pseudorandom number generators. We further propose a faster version of the proposed method and evaluate its security using the statistical tests of TestU01 published by L’Ecuyer and Simard.

scholarly journals Simple method of selecting totalistic rules for pseudorandom number generator based on nonuniform cellular automaton

2021 ◽  
Author(s):  
Miroslaw Szaban
Keyword(s):  
Cellular Automaton ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Large Set ◽  
Number Generator ◽  
Pseudorandom Sequences ◽  
Simple Method ◽  
One Dimensional ◽  
Simple Selection ◽  
Selection Of

AbstractThis paper is devoted to selecting rules for one-dimensional (1D) totalistic cellular automaton (TCA). These rules are used for the generation of pseudorandom sequences, which could be useful in cryptography. The power of pseudorandom number generator (PRNG) based on nonuniform TCA can be improved using not only one rule but a large set of rules. For this purpose, each subset of rules should be analyzed with its assignation to cellular automaton (CA) cells should be analyzed. We examine each of the subsets of totalistic rules, consisting of rules with neighborhood radius equal to 1 and 2. The entropy of bitstreams generated by the nonuniform TCA points out the best set of rules appropriate for the TCA-based generator. The paper also presents the method of simple selection of CA rules based on a cryptographic criterion known as a balance. The proposed method selects a maximal size of the set of available CA rules for a given neighborhood radius and suitable for PRNG. The method guarantees to avoid conflicting assignments of rules resulting in the creation of unwanted stable bit sequences, and provides high-quality pseudorandom sequences. This technique is used to verify the subsets of rules selected experimentally. Verified rules are proposed for 1D TCA-based PRNG as a new subset of best nonuniform TCA rules. New picked, examined, and verified subset of rules could be used in TCA-based PRNG and provide cryptographically strong bit sequences and huge keyspace.

scholarly journals Analisis Teoritis dan Empiris Uji Craps dari Diehard Battery of Randomness Test untuk Pengujian Pembangkit Bilangan Acaksemu

CAUCHY ◽  
2013 ◽  
Vol 2 (4) ◽  
pp. 216
Author(s):  
Sari Agustini Hafman ◽  
Arif Fachru Rozi
Keyword(s):  
Statistical Theory ◽  
Theoretical Analysis ◽  
Random Number ◽  
Statistical Tests ◽  
Random Number Generator ◽  
Pseudorandom Sequence ◽  
Number Generator ◽  
Test Statistic ◽  
Pseudorandom Sequences ◽  
Randomness Test

According to Kerchoffs (1883), the security system should only rely on cryptographic keys which is used in that system. Generally, the key sequences are generated by a Pseudo Random Number Generator (PRNG) or Random Number Generator (RNG). There are three types of randomness sequences that generated by the RNG and PRNG i.e. pseudorandom sequence, cryptographically secure pseudorandom sequences, and real random sequences. Several statistical tests, including diehard battery of tests of randomness, is used to check the type of randomness sequences that generated by PRNG or RNG. Due to its purpose, the principle on taking the testing parameters and the test statistic are associated with the validity of the conclusion produced by a statistical test, then the theoretical analysis is performed by applying a variety of statistical theory to evaluate craps test, one of the test included in the diehard battery of randomness tests. Craps test, inspired by craps game, aims to examine whether a PRNG produces an independent and identically distributed (iid) pseudorandom sequences. To demonstrate the process to produce a test statistics equation and to show how craps games applied on that test, will be carried out theoretical analysis by applying a variety of statistical theory. Furthermore, empirical observations will be done by applying craps test on a PRNG in order to check the test effectiveness in detecting the distribution and independency of sequences which produced by PRNG

scholarly journals High Throughput Pseudorandom Number Generator Based on Variable Argument Unified Hyperchaos

VLSI Design ◽  
2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Kaiyu Wang ◽  
Qingxin Yan ◽  
Shihua Yu ◽  
Xianwei Qi ◽  
Yudi Zhou ◽  
...  
Keyword(s):  
High Throughput ◽  
Standard Test ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Hyperchaotic System ◽  
Number Generator ◽  
Maximum Throughput ◽  
Verilog Hdl ◽  
Pseudorandom Sequences ◽  
Different Chaotic Systems

This paper presents a new multioutput and high throughput pseudorandom number generator. The scheme is to make the homogenized Logistic chaotic sequence as unified hyperchaotic system parameter. So the unified hyperchaos can transfer in different chaotic systems and the output can be more complex with the changing of homogenized Logistic chaotic output. Through processing the unified hyperchaotic 4-way outputs, the output will be extended to 26 channels. In addition, the generated pseudorandom sequences have all passed NIST SP800-22 standard test and DIEHARD test. The system is designed in Verilog HDL and experimentally verified on a Xilinx Spartan 6 FPGA for a maximum throughput of 16.91 Gbits/s for the native chaotic output and 13.49 Gbits/s for the resulting pseudorandom number generators.

scholarly journals Yet Another Pseudorandom Number Generator

2017 ◽  
Vol 63 (2) ◽  
pp. 195-199 ◽  
Author(s):  
Borislav Stoyanov ◽  
Krzysztof Szczypiorski ◽  
Krasimir Kordov
Keyword(s):  
Boolean Function ◽  
Data Security ◽  
Statistical Tests ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Number Generation ◽  
Pseudorandom Number Generation ◽  
High Level

Abstract We propose a novel pseudorandom number generator based on R¨ossler attractor and bent Boolean function. We estimated the output bits properties by number of statistical tests. The results of the cryptanalysis show that the new pseudorandom number generation scheme provides a high level of data security.

A Test of Minitab's Pseudorandom-Number Generator

1986 ◽  
Vol 63 (3) ◽  
pp. 1319-1322
Author(s):  
F. Richard Ferraro
Keyword(s):  
Statistical Tests ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Educational Settings ◽  
Computer Package ◽  
Standard Tests

The reliability of Minitab's pseudorandom-number generator was investigated. Minitab, an interactive statistical computer package, allows the user a variety of statistical tests and analyses. Standard tests of randomness were performed; results indicated that numbers generated by Minitab are suitably random for use in business or educational settings.

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